Matching Items (5)
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- All Subjects: power flow
- All Subjects: Battery
- Creators: Hedman, Kory W
- Member of: Theses and Dissertations
- Status: Published
Description
Due to great challenges from aggressive environmental regulations, increased demand due to new technologies and the integration of renewable energy sources, the energy industry may radically change the way the power system is operated and designed. With the motivation of studying and planning the future power system under these new challenges, the development of the new tools is required. A network equivalent that can be used in such planning tools needs to be generated based on an accurate power flow model and an equivalencing procedure that preserves the key characteristics of the original system. Considering the pervasive use of the dc power flow models, their accuracy is of great concern. The industry seems to be sanguine about the performance of dc power flow models, but recent research has shown that the performance of different formulations is highly variable. In this thesis, several dc power-flow models are analyzed theoretically and evaluated numerically in IEEE 118-bus system and Eastern Interconnection 62,000-bus system. As shown in the numerical example, the alpha-matching dc power flow model performs best in matching the original ac power flow solution. Also, the possibility of applying these dc models in the various applications has been explored and demonstrated. Furthermore, a novel hot-start optimal dc power-flow model based on ac power transfer distribution factors (PTDFs) is proposed, implemented and tested. This optimal-reactance-only dc model not only matches the original ac PF solution well, but also preserves the congestion pattern obtain from the OPF results of the original ac model. Three improved strategies were proposed for applying the bus-aggregation technique to the large-scale systems, like EI and ERCOT, to improve the execution time, and memory requirements when building a reduced equivalent model. Speed improvements of up to a factor of 200 were observed.
ContributorsQi, Yingying (Author) / Tylavsky, Daniel J (Thesis advisor) / Hedman, Kory W (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2013
Description
As global energy demand has dramatically increased and traditional fossil fuels will be depleted in the foreseeable future, clean and unlimited renewable energies are recognized as the future global energy challenge solution. Today, the power grid in U.S. is building more and more renewable energies like wind and solar, while the electric power system faces new challenges from rapid growing percentage of wind and solar. Unlike combustion generators, intermittency and uncertainty are the inherent features of wind and solar. These features bring a big challenge to the stability of modern electric power grid, especially for a small scale power grid with wind and solar. In order to deal with the intermittency and uncertainty of wind and solar, energy storage systems are considered as one solution to mitigate the fluctuation of wind and solar by smoothing their power outputs. For many different types of energy storage systems, this thesis studied the operation of battery energy storage systems (BESS) in power systems and analyzed the benefits of the BESS. Unlike many researchers assuming fixed utilization patterns for BESS and calculating the benefits, this thesis found the BESS utilization patterns and benefits through an investment planning model. Furthermore, a cost is given for utilizing BESS and to find the best way of operating BESS rather than set an upper bound and a lower bound for BESS energy levels. Two planning models are proposed in this thesis and preliminary conclusions are derived from simulation results. This work is organized as below: chapter 1 briefly introduces the background of this research; chapter 2 gives an overview of previous related work in this area; the main work of this thesis is put in chapter 3 and chapter 4 contains the generic BESS model and the investment planning model; the following chapter 5 includes the simulation and results analysis of this research and chapter 6 provides the conclusions from chapter 5.
ContributorsDai, Daihong (Author) / Hedman, Kory W (Thesis advisor) / Zhang, Muhong (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis addresses the issue of making an economic case for bulk energy storage in the Arizona bulk power system. Pumped hydro energy storage (PHES) is used in this study. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load (store energy when it is inexpensive [energy demand is low] and discharge energy when it is expensive [energy demand is high]). It also has the potential to provide opportunities to avoid transmission and generation expansion, and provide for generation reserve margins. As the level of renewable energy resources increases, the uncertainty and variability of wind and solar resources may be improved by bulk energy storage technologies.
For this study, the MATLab software platform is used, a mathematical based modeling language, optimization solvers (specifically Gurobi), and a power flow solver (PowerWorld) are used to simulate an economic dispatch problem that includes energy storage and transmission losses. A program is created which utilizes quadratic programming to analyze various cases using a 2010 summer peak load from the Arizona portion of the Western Electricity Coordinating Council (WECC) system. Actual data from industry are used in this test bed. In this thesis, the full capabilities of Gurobi are not utilized (e.g., integer variables, binary variables). However, the formulation shown here does create a platform such that future, more sophisticated modeling may readily be incorporated.
The developed software is used to assess the Arizona test bed with a low level of energy storage to study how the storage power limit effects several optimization outputs such as the system wide operating costs. Large levels of energy storage are then added to see how high level energy storage affects peak shaving, load factor, and other system applications. Finally, various constraint relaxations are made to analyze why the applications tested eventually approach a constant value. This research illustrates the use of energy storage which helps minimize the system wide generator operating cost by "shaving" energy off of the peak demand.
The thesis builds on the work of another recent researcher with the objectives of strengthening the assumptions used, checking the solutions obtained, utilizing higher level simulation languages to affirm results, and expanding the results and conclusions.
One important point not fully discussed in the present thesis is the impact of efficiency in the pumped hydro cycle. The efficiency of the cycle for modern units is estimated at higher than 90%. Inclusion of pumped hydro losses is relegated to future work.
For this study, the MATLab software platform is used, a mathematical based modeling language, optimization solvers (specifically Gurobi), and a power flow solver (PowerWorld) are used to simulate an economic dispatch problem that includes energy storage and transmission losses. A program is created which utilizes quadratic programming to analyze various cases using a 2010 summer peak load from the Arizona portion of the Western Electricity Coordinating Council (WECC) system. Actual data from industry are used in this test bed. In this thesis, the full capabilities of Gurobi are not utilized (e.g., integer variables, binary variables). However, the formulation shown here does create a platform such that future, more sophisticated modeling may readily be incorporated.
The developed software is used to assess the Arizona test bed with a low level of energy storage to study how the storage power limit effects several optimization outputs such as the system wide operating costs. Large levels of energy storage are then added to see how high level energy storage affects peak shaving, load factor, and other system applications. Finally, various constraint relaxations are made to analyze why the applications tested eventually approach a constant value. This research illustrates the use of energy storage which helps minimize the system wide generator operating cost by "shaving" energy off of the peak demand.
The thesis builds on the work of another recent researcher with the objectives of strengthening the assumptions used, checking the solutions obtained, utilizing higher level simulation languages to affirm results, and expanding the results and conclusions.
One important point not fully discussed in the present thesis is the impact of efficiency in the pumped hydro cycle. The efficiency of the cycle for modern units is estimated at higher than 90%. Inclusion of pumped hydro losses is relegated to future work.
ContributorsDixon, William Jesse J (Author) / Heydt, Gerald T (Thesis advisor) / Hedman, Kory W (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Synthetic power system test cases offer a wealth of new data for research and development purposes, as well as an avenue through which new kinds of analyses and questions can be examined. This work provides both a methodology for creating and validating synthetic test cases, as well as a few use-cases for how access to synthetic data enables otherwise impossible analysis.
First, the question of how synthetic cases may be generated in an automatic manner, and how synthetic samples should be validated to assess whether they are sufficiently ``real'' is considered. Transmission and distribution levels are treated separately, due to the different nature of the two systems. Distribution systems are constructed by sampling distributions observed in a dataset from the Netherlands. For transmission systems, only first-order statistics, such as generator limits or line ratings are sampled statistically. The task of constructing an optimal power flow case from the sample sets is left to an optimization problem built on top of the optimal power flow formulation.
Secondly, attention is turned to some examples where synthetic models are used to inform analysis and modeling tasks. Co-simulation of transmission and multiple distribution systems is considered, where distribution feeders are allowed to couple transmission substations. Next, a distribution power flow method is parametrized to better account for losses. Numerical values for the parametrization can be statistically supported thanks to the ability to generate thousands of feeders on command.
First, the question of how synthetic cases may be generated in an automatic manner, and how synthetic samples should be validated to assess whether they are sufficiently ``real'' is considered. Transmission and distribution levels are treated separately, due to the different nature of the two systems. Distribution systems are constructed by sampling distributions observed in a dataset from the Netherlands. For transmission systems, only first-order statistics, such as generator limits or line ratings are sampled statistically. The task of constructing an optimal power flow case from the sample sets is left to an optimization problem built on top of the optimal power flow formulation.
Secondly, attention is turned to some examples where synthetic models are used to inform analysis and modeling tasks. Co-simulation of transmission and multiple distribution systems is considered, where distribution feeders are allowed to couple transmission substations. Next, a distribution power flow method is parametrized to better account for losses. Numerical values for the parametrization can be statistically supported thanks to the ability to generate thousands of feeders on command.
ContributorsSchweitzer, Eran (Author) / Scaglione, Anna (Thesis advisor) / Hedman, Kory W (Committee member) / Overbye, Thomas J (Committee member) / Monti, Antonello (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2019
Description
Lithium ion batteries are quintessential components of modern life. They are used to power smart devices — phones, tablets, laptops, and are rapidly becoming major elements in the automotive industry. Demand projections for lithium are skyrocketing with production struggling to keep up pace. This drive is due mostly to the rapid adoption of electric vehicles; sales of electric vehicles in 2020 are more than double what they were only a year prior. With such staggering growth it is important to understand how lithium is sourced and what that means for the environment. Will production even be capable of meeting the demand as more industries make use of this valuable element? How will the environmental impact of lithium affect growth? This thesis attempts to answer these questions as the world looks to a decade of rapid growth for lithium ion batteries.
ContributorsMelton, John (Author) / Brian, Jennifer (Thesis director) / Karwat, Darshawn (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05